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Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019

In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is co...

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Autores principales: Liu, Hui, Lin, Shujin, Ao, Xiulan, Gong, Xiangwen, Liu, Chunyun, Xu, Dechang, Huang, Yumei, Liu, Zhiqiang, Zhao, Bixing, Liu, Xiaolong, Han, Xiao, Ye, Hanhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836900/
https://www.ncbi.nlm.nih.gov/pubmed/33520118
http://dx.doi.org/10.1016/j.csbj.2020.12.010
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author Liu, Hui
Lin, Shujin
Ao, Xiulan
Gong, Xiangwen
Liu, Chunyun
Xu, Dechang
Huang, Yumei
Liu, Zhiqiang
Zhao, Bixing
Liu, Xiaolong
Han, Xiao
Ye, Hanhui
author_facet Liu, Hui
Lin, Shujin
Ao, Xiulan
Gong, Xiangwen
Liu, Chunyun
Xu, Dechang
Huang, Yumei
Liu, Zhiqiang
Zhao, Bixing
Liu, Xiaolong
Han, Xiao
Ye, Hanhui
author_sort Liu, Hui
collection PubMed
description In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases.
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spelling pubmed-78369002021-01-26 Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019 Liu, Hui Lin, Shujin Ao, Xiulan Gong, Xiangwen Liu, Chunyun Xu, Dechang Huang, Yumei Liu, Zhiqiang Zhao, Bixing Liu, Xiaolong Han, Xiao Ye, Hanhui Comput Struct Biotechnol J Research Article In coronavirus disease 2019 (COVID-19) patients, interleukin (IL)-6 is one of the leading factors causing death through cytokine release syndrome. Hence, identification of IL-6 downstream from clinical patients’ transcriptome is very valid for analyses of its mechanism. However, clinical study is conditional and time consuming to collect optional size of samples, as patients have the clinical heterogeneity. A possible solution is to deeply mine the relative existing data. Several transcriptome-based studies on other diseases or treatments have revealed different genes to be regulated by IL-6. Through our meta-analysis of these transcriptome datasets, 352 genes were suggested to be regulated by IL-6 in different biological conditions, some of which were related to virus infection and cardiovascular disease. Among them, 232 genes were not identified by current transcriptome studies from clinical research. ICAM1 and PFKFB3 were the most significantly upregulated genes in our meta-analysis and could be employed as biomarkers in patients with severe COVID-19. In general, a meta-analysis of transcriptome datasets could be an alternative way to analyze the immune response and complications of patients suffering from severe COVID-19 and other emergency diseases. Research Network of Computational and Structural Biotechnology 2020-12-24 /pmc/articles/PMC7836900/ /pubmed/33520118 http://dx.doi.org/10.1016/j.csbj.2020.12.010 Text en © 2021 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Liu, Hui
Lin, Shujin
Ao, Xiulan
Gong, Xiangwen
Liu, Chunyun
Xu, Dechang
Huang, Yumei
Liu, Zhiqiang
Zhao, Bixing
Liu, Xiaolong
Han, Xiao
Ye, Hanhui
Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title_full Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title_fullStr Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title_full_unstemmed Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title_short Meta-analysis of transcriptome datasets: An alternative method to study IL-6 regulation in coronavirus disease 2019
title_sort meta-analysis of transcriptome datasets: an alternative method to study il-6 regulation in coronavirus disease 2019
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7836900/
https://www.ncbi.nlm.nih.gov/pubmed/33520118
http://dx.doi.org/10.1016/j.csbj.2020.12.010
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